171 million names (100 million unique) This torrent contains: The URL of every searchable Facebook user s profile The name of every searchable Facebook user, both unique and by count (perfect for post-processing, datamining, etc) Processed lists, including first names with count, last names with count, potential usernames with count, etc The programs I used to generate everything So, there you have it: lots of awesome data from Facebook. Now, I just have to find one more problem with Facebook so I can write "Revenge of the Facebook Snatchers" and complete the trilogy. Any suggestions? >:-) Limitations So far, I have only indexed the searchable users, not their friends. Getting their friends will be significantly more data to process, and I don t have those capabilities right now. I d like to tackle that in the future, though, so if anybody has any bandwidth they d like to donate, all I need is an ssh account and Nmap installed. An additional limitation is that these are on

The Most Followed Facebook Accounts dataset provides information on the accounts with the highest number of followers on the Facebook platform. It includes data on various public figures, celebrities, organizations, and brands that have amassed a significant following, showcasing their popularity and influence on the social media platform.

Facebook is becoming an essential tool for more than just family and friends. Discover how Cheltenham Township (USA), a diverse community just outside of Philadelphia, deals with major issues such as the Bill Cosby trial, everyday traffic issues, sewer I/I problems and lost cats and dogs. And yes, theft.

Communities work when they're connected and exchanging information. What and who are the essential forces making a positive impact, and when and how do conversational threads get directed or misdirected?

Use Any Facebook Public Group

You can leverage the examples here for any public Facebook group. For an example of the source code used to collect this data, and a quick start docker image, take a look at the following project: facebook-group-scrape.

Data Sources

There are 4 csv files in the dataset, with data from the following 5 public Facebook groups:

• Unofficial Cheltenham Township
• Elkins Park Happenings!
• Free Speech Zone
• Cheltenham Lateral Solutions
• Cheltenham Township Residents

post.csv

These are the main posts you will see on the page. It might help to take a quick look at the page. Commas in the msg field have been replaced with {COMMA}, and apostrophes have been replaced with {APOST}.

• gid Group id (5 different Facebook groups)
• pid Main Post id
• id Id of the user posting
• name User's name
• timeStamp
• shares
• url
• msg Text of the message posted.
• likes Number of likes

comment.csv

These are comments to the main post. Note, Facebook postings have comments, and comments on comments.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Comment Id.
• timeStamp
• id Id of user commenting
• name Name of user commenting
• rid Id of user responding to first comment
• msg Message

like.csv

These are likes and responses. The two keys in this file (pid,cid) will join to post and comment respectively.

• gid Group id
• pid Matches Main Post identifier in post.csv
• cid Matches Comments id.
• response Response such as LIKE, ANGRY etc.
• id The id of user responding
• name Name of the user responding

member.csv

These are all the members in the group. Some members never, or rarely, post or comment. You may find multiple entries in this table for the same person. The name of the individual never changes, but they change their profile picture. Each profile picture change is captured in this table. Facebook gives users a new id in this table when they change their profile picture.

• gid Group id
• id Id of the member
• name Name of the member
• url URL of the member

Access our extensive Facebook datasets that provide detailed information on public posts, pages, and user engagement. Gain insights into post performance, audience interactions, page details, and content trends with our ethically sourced data. Free samples are available for evaluation. Over 940M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Post ID Post Content & URL Date Posted Hashtags Number of Comments Number of Shares Likes & Reaction Counts (by type) Video View Count Page Name & Category Page Followers & Likes Page Verification Status Page Website & Contact Info Is Sponsored Post Attachments (Images/Videos) External Link Data And much more

The global number of Facebook users was forecast to continuously increase between 2023 and 2027 by in total 391 million users (+14.36 percent). After the fourth consecutive increasing year, the Facebook user base is estimated to reach 3.1 billion users and therefore a new peak in 2027. Notably, the number of Facebook users was continuously increasing over the past years. User figures, shown here regarding the platform Facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

The LiLaH-HAG dataset (HAG is short for hate-age-gender) consists of metadata on Facebook comments to Facebook posts of mainstream media in Great Britain, Flanders, Slovenia and Croatia. The metadata available in the dataset are the hatefulness of the comment (0 is acceptable, 1 is hateful), age of the commenter (0-25, 26-30, 36-65, 65-), gender of the commenter (M or F), and the language in which the comment was written (EN, NL, SL, HR).

The hatefulness of the comment was assigned by multiple well-trained annotators by reading comments in the order of appearance in a discussion thread, while the age and gender variables were estimated from the Facebook profile of a specific user by a single annotator.

The number of Facebook users in India was forecast to continuously increase between 2024 and 2028 by in total **** million users (+*** percent). After the ninth consecutive increasing year, the Facebook user base is estimated to reach ****** million users and therefore a new peak in 2028. Notably, the number of Facebook users of was continuously increasing over the past years.User figures, shown here regarding the platform facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of Facebook users in countries like Nepal and Pakistan.

This statistical dataset contains estimates on the number of active online Facebook users living outside of their country of origin within the European Union. The dataset includes information on Facebook users' age, gender, country of residence, and country of previous residence. The data is divided in the number of Monthly Active Users and Daily Active Users. The data was collected through standard CSV format via an advertising API platform by using an R Studio code, and the data collection was conducted twice a month from January to November 2021. The dataset was originally published in DiVA and moved to SND in 2024. Detta statistiska dataset innehåller uppskattningar av antalet aktiva Facebook-användare online som bor utanför sitt ursprungsland inom Europeiska unionen. Se engelsk beskrivning för mer information. Datasetet har ursprungligen publicerats i DiVA och flyttades över till SND 2024.

Dataset used in Article "Identification and characterization of Facebook user profiles considering interaction aspects"

The Facebook Users by Country Data (Cleaned) dataset is a collection of information on Facebook users from different countries. The dataset contains five columns of data, which are named as follows:

• Names: This column contains the names of the countries for which the data is collected.
• Users: This column provides the number of Facebook users in millions for each respective country.
• Facebook_Users: This column shows the percentage of the total population of each country that uses Facebook.
• Date_of_Data: This column indicates the date on which the data was collected and compiled.
• Population: This column represents the total population of each country.

How you can use this Dataset?

The Facebook Users by Country Data (Cleaned) dataset can be used in several ways. Here are some potential use cases:

• Market Research: Marketers can use this dataset to identify markets with the highest concentration of Facebook users. This information can be used to target Facebook ads to specific regions, optimize social media campaigns, and determine which markets to expand into.

• Business Strategy: Businesses can use this dataset to identify potential markets for their products or services. By analyzing Facebook usage rates in different countries, businesses can identify countries with high engagement rates and target those markets.

• Social Media Analysis: Researchers can use this dataset to analyze social media behavior in different countries. By comparing Facebook usage rates across different countries, researchers can identify cultural and social differences that affect social media behavior.

Use our Facebook Posts dataset to access detailed information about individual Facebook posts, including content, hashtags, engagement metrics, and page details like name, category, and followers. Popular use cases include analyzing user engagement, tracking content trends, and studying page dynamics for strategic insights. Over 31M records available Price starts at $250/100K records Data formats are available in JSON, NDJSON, CSV, XLSX and Parquet. 100% ethical and compliant data collection Included datapoints:

Post ID Post Content & URL Date Posted Hashtags Number of Comments Number of Shares Likes & Reaction Counts (by type) Video View Count Page Name & Category Page Followers & Likes Page Verification Status Page Website & Contact Info Is Sponsored Post Attachments (Images/Videos) External Link Data And much more

Which county has the most Facebook users?

              There are more than 378 million Facebook users in India alone, making it the leading country in terms of Facebook audience size. To put this into context, if India’s Facebook audience were a country then it would be ranked third in terms of largest population worldwide. Apart from India, there are several other markets with more than 100 million Facebook users each: The United States, Indonesia, and Brazil with 193.8 million, 119.05 million, and 112.55 million Facebook users respectively.

              Facebook – the most used social media

              Meta, the company that was previously called Facebook, owns four of the most popular social media platforms worldwide, WhatsApp, Facebook Messenger, Facebook, and Instagram. As of the third quarter of 2021, there were around 3,5 billion cumulative monthly users of the company’s products worldwide. With around 2.9 billion monthly active users, Facebook is the most popular social media worldwide. With an audience of this scale, it is no surprise that the vast majority of Facebook’s revenue is generated through advertising.

              Facebook usage by device
              As of July 2021, it was found that 98.5 percent of active users accessed their Facebook account from mobile devices. In fact, almost 81.8 percent of Facebook audiences worldwide access the platform only via mobile phone. Facebook is not only available through mobile browser as the company has published several mobile apps for users to access their products and services. As of the third quarter 2021, the four core Meta products were leading the ranking of most downloaded mobile apps worldwide, with WhatsApp amassing approximately six billion downloads.

Aggregative qualitative data about the presence of bots (fake accounts) on pages of the most popular Ukrainian politicians and top-5 Ukrainian media during the parliamentary elections campaign in 2019.

The number of Facebook users in Indonesia was forecast to continuously decrease between 2024 and 2028 by in total ** million users (-***** percent). According to this forecast, in 2028, the Facebook user base will have decreased for the fifth consecutive year to ****** million users. User figures, shown here regarding the platform facebook, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find further information concerning Thailand and Singapore.

Facebook uses an anonymized snapshot of all active Facebook users and their friendship networks to measure the intensity of connectedness between locations. The Social Connectedness Index (SCI) is a measure of the social connectedness between different geographies. Specifically, it measures the relative probability that two individuals across two locations are friends with each other on Facebook. Region identifiers are taken from GADM v2.8 https://gadm.org/download_country_v2.html.

The study on Facebook users was conducted by infratest dimap on behalf of the Konrad Adenauer Foundation. During the survey period from November 26 to December 4, 2018, 2,041 Facebook users were surveyed in online interviews (CAWI) on the following topics: internet use, Facebook groups, Facebook use, political content on Facebook, reaction to content, image experiment and Sunday question. Respondents were selected by quota sampling from an online access panel. Use of various internet services (Tinder, Facebook, Twitter, snapchat, Instagram, YouTube, online newspapers, none of the above); use of open or closed Facebook groups; Facebook content on political topics, on job-related topics, on hobbies, on entertainment or on other topics; type of Facebook use (read/ like/ share content, write comments, disseminate own content); political Facebook use (read/ like/ share political content, write comments on political topics, disseminate own content on political topics); reaction to Facebook content or comments (do I feel informed, entertained, annoyed, provoked, etc.). comments (feel informed, entertained, annoyed, provoked); agreement with various statements on Facebook (on Facebook others upset me, I show others their limits, I can speak my mind anonymously, I find many different opinions, I find opinions that are otherwise suppressed, I dare to say/ share things I would not otherwise say); party preference (Sunday question); comment (open) on a provocative image (split A: refugees, split B: Pegida). Demography: sex; age (year of birth); education; employment; occupational status; net household income (grouped); federal state. Additionally coded: serial number; weighting factor. Die Studie über Facebook-Nutzer wurde von infratest dimap im Auftrag der Konrad-Adenauer-Stiftung durchgeführt. Im Erhebungszeitraum 26. November bis 4. Dezember 2018 wurden 2.041 Facebook-Nutzer in Onlineinterviews (CAWI) zu folgenden Themen befragt: Internetnutzung, Facebook-Gruppen, Facebooknutzung, politische Inhalte auf Facebook, Reaktion auf Inhalte, Bildexperiment und Sonntagsfrage. Die Auswahl der Befragten erfolgte durch eine Quotenstichprobe aus einem Online-Access-Panel. Nutzung verschiedener Internetangebote (Tinder, Facebook, Twitter, snapchat, Instagram, YouTube, Online-Zeitungen, nichts davon); Nutzung offener oder geschlossener Facebook-Gruppen; Facebook-Inhalte zu politischen Themen, zu berufsbezogenen Themen, zu Hobbies, zur Unterhaltung bzw. zu anderen Themen; Art der Facebook-Nutzung (lese/ like/ teile Inhalte, schreibe Kommentare, verbreite eigene Inhalte); politische Facebook-Nutzung (lese/ like/ teile politische Inhalte, schreibe Kommentare zu politischen Themen, verbreite eigenen Inhalt zu politischen Themen); Reaktion auf Facebook- Inhalte bzw. Kommentare (fühle mich informiert, unterhalten, verärgert, provoziert); Zustimmung zu verschiedenen Aussagen zu Facebook (auf Facebook regen mich andere auf, zeige ich anderen ihre Grenzen, kann ich anonym meine Meinung sagen, finde ich viele verschiedene Meinungen, finde ich Meinungen, die sonst unterdrückt werden, traue ich mich Dinge zu sagen/ teilen, die ich sonst nicht sagen würde); Parteipräferenz (Sonntagsfrage); Kommentar (offen) zu einem provozierenden Bild (Split A: Flüchtlinge, Split B: Pegida). Demographie: Geschlecht; Alter (Geburtsjahr); Bildung; Erwerbstätigkeit; berufliche Stellung; Haushaltsnettoeinkommen (gruppiert); Bundesland. Zusätzlich verkodet wurde: lfd. Nummer; Gewichtungsfaktor.

Gain valuable insights with our comprehensive Social Media Dataset, designed to help businesses, marketers, and analysts track trends, monitor engagement, and optimize strategies. This dataset provides structured and reliable social media data from multiple platforms.

Dataset Features

User Profiles: Access public social media profiles, including usernames, bios, follower counts, engagement metrics, and more. Ideal for audience analysis, influencer marketing, and competitive research. Posts & Content: Extract posts, captions, hashtags, media (images/videos), timestamps, and engagement metrics such as likes, shares, and comments. Useful for trend analysis, sentiment tracking, and content strategy optimization. Comments & Interactions: Analyze user interactions, including replies, mentions, and discussions. This data helps brands understand audience sentiment and engagement patterns. Hashtag & Trend Tracking: Monitor trending hashtags, topics, and viral content across platforms to stay ahead of industry trends and consumer interests.

Customizable Subsets for Specific Needs Our Social Media Dataset is fully customizable, allowing you to filter data based on platform, region, keywords, engagement levels, or specific user profiles. Whether you need a broad dataset for market research or a focused subset for brand monitoring, we tailor the dataset to your needs.

Popular Use Cases

Brand Monitoring & Reputation Management: Track brand mentions, customer feedback, and sentiment analysis to manage online reputation effectively. Influencer Marketing & Audience Analysis: Identify key influencers, analyze engagement metrics, and optimize influencer partnerships. Competitive Intelligence: Monitor competitor activity, content performance, and audience engagement to refine marketing strategies. Market Research & Consumer Insights: Analyze social media trends, customer preferences, and emerging topics to inform business decisions. AI & Predictive Analytics: Leverage structured social media data for AI-driven trend forecasting, sentiment analysis, and automated content recommendations.

Whether you're tracking brand sentiment, analyzing audience engagement, or monitoring industry trends, our Social Media Dataset provides the structured data you need. Get started today and customize your dataset to fit your business objectives.

Mutually liked facebook pages. Nodes represent the pages and edges are mutual likes among them. - Data collected about Facebook pages (November 2017). These datasets represent blue verified Facebook page networks of different categories. Nodes represent the pages and edges are mutual likes among them.

OverviewThe BuzzFeed dataset, officially known as the BuzzFeed-Webis Fake News Corpus 2016, comprises content from 9 news publishers over a 7-day period close to the 2016 US election. It was created to analyze the spread of misinformation and hyperpartisan content on social media platforms, particularly Facebook.Dataset CompositionNews Articles: The dataset includes 1,627 articles from various sources:826 from mainstream publishers256 from left-wing publishers545 from right-wing publishersFacebook Posts: Each article is associated with Facebook post data, including metrics like share counts, reaction counts, and comment counts.Comments: The dataset includes nearly 1.7 million Facebook comments discussing the news content.Fact-Check Ratings: Each article was fact-checked by professional journalists at BuzzFeed, providing veracity assessments.Key FeaturesPublisher Information: The dataset covers 9 publishers, including 6 hyperpartisan (3 left-wing and 3 right-wing) and 3 mainstream outlets.Temporal Aspect: The data was collected over seven weekdays (September 19-23 and September 26-27, 2016).Verification Status: All publishers included in the dataset had earned Facebook's blue checkmark, indicating authenticity and elevated status.Metadata: Includes various metrics such as publication dates, post types, and engagement statistics.Potential ApplicationsThe BuzzFeed dataset is valuable for various research and analytical purposes:News Veracity Assessment: Researchers can use machine learning techniques to classify articles based on their factual accuracy.Social Media Analysis: The dataset allows for studying how news spreads on platforms like Facebook, including engagement patterns.Hyperpartisan Content Study: It enables analysis of differences between mainstream and hyperpartisan news sources.Content Strategy Optimization: Media companies can use insights from the dataset to refine their content strategies.Audience Analysis: The data can be used for demographic analysis and audience segmentation.This dataset provides a comprehensive snapshot of news dissemination and engagement on social media during a crucial period, making it a valuable resource for researchers, data scientists, and media analysts studying online information ecosystems.

This dataset is compiled using this dataset from GitHub.

Data Description Table